Top Tech Jobs & Startup Jobs

Provides technical leadership for large-scale data platforms and distributed systems. Designs scalable backend services, batch and streaming architectures, workflow orchestration, cloud-native infrastructure, and data platform capabilities. Leads architecture decisions, migrations, reliability and performance improvements, technical standards, and cross-team initiatives. Mentors senior engineers and remains hands-on with Java, Python, Spark, Flink, Hadoop, Airflow, Kubernetes, and related technologies.

Architect and develop highly scalable block, file, and object storage systems for Kubernetes environments. Build distributed data-plane and control-plane components, write production code, optimize performance and resource efficiency, and ensure high availability, durability, replication, fault tolerance, and recovery. Debug issues across Linux, Kubernetes, networking, and storage layers while participating in architecture and code reviews and mentoring engineers.

Architect and develop eBay’s large-scale Hadoop infrastructure, including HDFS, Spark, YARN/YuniKorn, and modern data formats. Lead distributed-system scalability, high availability, performance tuning, cluster management, data governance, developer tooling, and enterprise ecosystem integration. Deliver reliable, fault-tolerant infrastructure and complex data-processing platforms for petabyte-scale, mission-critical applications.

Design, architect, and build highly scalable Block, File, and Object Storage platforms in Kubernetes environments. Develop production-grade storage software using C/C++, Go, or Rust, optimize data-plane and control-plane components, and solve complex issues across Linux, networking, Kubernetes, and storage layers. Lead architecture, technical roadmaps, cross-team initiatives, modernization, design reviews, production delivery, and mentoring while improving performance, reliability, scalability, and data durability.

Design, architect, and build highly scalable block, file, and object storage platforms in Kubernetes environments. Develop production-grade storage software using C/C++, Go, or Rust; optimize data-plane and control-plane components; and debug issues across Linux, networking, Kubernetes, and storage layers. Lead architecture, technical roadmaps, cross-team initiatives, modernization, and production delivery while mentoring engineers and improving reliability, performance, scalability, and durability.

Own production LLM inference systems from model handoff through serving, optimizing latency, throughput, GPU utilization, memory, and cost. Operate heterogeneous GPU fleets, tune vLLM and Triton-based runtimes, build benchmarking and observability tools, improve reliability, and respond to incidents. Apply inference optimizations such as quantization, batching, KV-cache management, and runtime improvements. Partner with data science and product teams to establish performance and availability goals.

Architect and develop scalable block, file, and object storage systems for Kubernetes environments. Build distributed storage data-plane and control-plane components, write production code, optimize performance, and ensure availability, replication, durability, and recovery. Debug issues across Linux, Kubernetes, networking, and storage layers. Participate in architecture and code reviews while mentoring engineers.

Design, build, and operate petabyte-scale distributed database platforms. Own complex initiatives involving storage, transactions, replication, consensus, scalability, availability, performance, and geo-distribution. Develop and review production code, troubleshoot difficult systems issues, guide architectural decisions, and support production operations. Mentor engineers, lead design and code reviews, collaborate with global teams and customers, and use AI coding tools to deliver high-quality software.

Design, build, and operate traffic management and routing systems for eBay’s large-scale commerce platforms. Develop high-performance services using Java, C++, or Go; deploy and troubleshoot Kubernetes workloads; improve security, latency, throughput, and reliability; and use observability tools for production diagnosis. Collaborate with SRE, platform, and application teams on distributed systems and networking solutions.

Conduct applied research on generative AI and foundation models, including LLMs, multimodal systems, agents, retrieval, post-training, and learning from feedback. Design experiments, develop and evaluate models, analyze large-scale marketplace data, and collaborate with engineering and product teams to productionize research. Contributions may include publications, patents, open-source work, and technical knowledge sharing.